We are seeking a highly skilled and visionary Lead Machine Learning (ML) Engineer to spearhead the development and deployment of innovative machine learning and large language model (LLM) solutions. In this pivotal role, you will lead a team of ML engineers and data scientists, driving impactful AI initiatives that support data-driven decision-making across a wide range of business functions.
You’ll be working in a dynamic, fast-paced environment that values collaboration, innovation, and continuous learning. This is a unique opportunity to take ownership of the full ML lifecycle, from ideation and design to production deployment and optimization, while shaping the strategic direction of our AI/ML capabilities.
Key Responsibilities
- Lead ML Projects End-to-End. Architect, design, and implement machine learning models that solve complex business problems and deliver measurable results.
- Team Leadership & Mentorship. Guide a high-performing team of ML engineers and data scientists. Provide technical mentorship, conduct code reviews, and foster a culture of innovation and continuous improvement.
- Business Collaboration. Work closely with stakeholders, product managers, and engineers to understand business requirements and translate them into scalable ML solutions.
- Model Optimization. Ensure that ML models are optimized for performance, scalability, latency, and accuracy. Continuously refine models based on feedback and performance metrics.
- Data Engineering. Design and implement robust data pipelines for data ingestion, cleaning, transformation, and feature engineering.
- Model Validation & Monitoring. Establish rigorous testing, validation, and monitoring strategies to ensure reliability and accuracy of ML systems in production.
- MLOps & Deployment. Collaborate with DevOps teams to integrate ML models into production environments using best practices in MLOps (CI/CD, versioning, monitoring).
- Innovation & Research. Stay abreast of the latest advancements in machine learning, deep learning, and LLMs. Evaluate and integrate emerging technologies as appropriate.
- Ethical AI Practices. Uphold high standards in AI ethics, data privacy, and model interpretability to ensure responsible use of machine learning.
Required Qualifications & Skills
Professional Experience
- 5–7 years of experience in machine learning engineering, including at least 3 years in a technical leadership role.
- Proven track record in building, deploying, and maintaining ML models in production.
Technical Expertise
- Strong proficiency in Python and at least one compiled language such as Java or C++.
- Deep understanding of machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers.
- Hands-on experience with LLMs, fine-tuning, prompt engineering, and transformer-based architectures.
Cloud & MLOps
- Practical experience with cloud platforms like AWS, Google Cloud Platform (GCP), or Microsoft Azure.
- Familiarity with MLOps tools and practices for model deployment, version control, and monitoring.
Collaboration & Communication
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong problem-solving abilities and a collaborative mindset.
Development Practices
Educational Background
- A Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related discipline is required.
- A Master’s or Ph.D. in Machine Learning, Artificial Intelligence, or a similar field is highly preferred and will be considered a strong asset.
What We Offer
- A collaborative and intellectually stimulating work environment.
- Opportunities to work on cutting-edge AI projects with real-world impact.
- Competitive compensation and performance-based incentives.
- Professional growth through mentorship, conferences, and learning programs.
- Flexible work arrangements and a focus on work-life balance.
- A diverse and inclusive culture that values every voice.
If you're passionate about driving innovation with machine learning and LLMs, thrive in a leadership role, and want to be part of a forward-thinking team that's shaping the future of AI, we'd love to hear from you.
Apply now and join us in building intelligent systems that make a real difference.